论文标题

快速预处理最佳正交范围报告和范围后继产品,并应用于文本索引

Fast Preprocessing for Optimal Orthogonal Range Reporting and Range Successor with Applications to Text Indexing

论文作者

Gao, Younan, He, Meng, Nekrich, Yakov

论文摘要

在RAM模型中,我们设计了可以在$ o(n \ sqrt {\ lg n})$ n $点以$ n \ times n $ grid中构建的三个数据结构。第一个数据结构是$ O(n \ lg^εn)$ - 单词结构支持$ O(\ lg \ lg n+k)$ time中的正交范围报告,其中$ k $表示输出大小,$ε$是任意的小常数。第二个是$ O(n \ lg \ lg n)$ - 单词结构,支持$ O(\ lg \ lg n)$时间的正交范围后继时间,而第三个是$ O(n \ lg^εn)$ - 单词结构 - 支持排序范围的$ O(\ lg \ lg \ lg n+k)$ time。当空间成本必须在$ o(n \ polylog \ n)$单词之内时,这些数据结构的查询时间是最佳的。它们的确切空间界限与达到相同查询时间的最著名结果相匹配,而$ O(n \ sqrt {\ lg n})$构造时间击败了预处理的先前界限。以前,在2D范围搜索结构中,只有Chan和Pǎtraşcu的正交范围计数结构(Soda 2010)和线性空间,$ O(\ lg^εN)$(belazzougui和Puglisi(Soda 2016)的正交范围后代的查询时间结构可以在同一$(SODA 2016)中建立。因此,我们的工作是第一个为最佳正交范围报告和范围后继者实现相同预处理时间的工作。我们还应用结果来改善文本索引的构建时间。

Under the word RAM model, we design three data structures that can be constructed in $O(n\sqrt{\lg n})$ time over $n$ points in an $n \times n$ grid. The first data structure is an $O(n\lg^ε n)$-word structure supporting orthogonal range reporting in $O(\lg\lg n+k)$ time, where $k$ denotes output size and $ε$ is an arbitrarily small constant. The second is an $O(n\lg\lg n)$-word structure supporting orthogonal range successor in $O(\lg\lg n)$ time, while the third is an $O(n\lg^ε n)$-word structure supporting sorted range reporting in $O(\lg\lg n+k)$ time. The query times of these data structures are optimal when the space costs must be within $O(n\ polylog\ n)$ words. Their exact space bounds match those of the best known results achieving the same query times, and the $O(n\sqrt{\lg n})$ construction time beats the previous bounds on preprocessing. Previously, among 2d range search structures, only the orthogonal range counting structure of Chan and Pǎtraşcu (SODA 2010) and the linear space, $O(\lg^ε n)$ query time structure for orthogonal range successor by Belazzougui and Puglisi (SODA 2016) can be built in the same $O(n\sqrt{\lg n})$ time. Hence our work is the first that achieve the same preprocessing time for optimal orthogonal range reporting and range successor. We also apply our results to improve the construction time of text indexes.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源